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Images_for_technical_poster.py
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Images_for_technical_poster.py
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import matplotlib.pyplot as plt
import cmos
import numpy as np
import cv2
import sklearn.preprocessing
def save_orig_image(sky_imager,output_folder,output_name="original_image.png"):
image = sky_imager.original_image.copy()
image = image[:,:,::-1]
cv2.imshow("asdf",image)
cv2.waitKey(0)
cv2.imwrite(output_folder+output_name, image)
print("Saved original image at: " +output_folder + output_name )
def save_crop_mask(sky_imager,output_folder,output_name="crop_mask.png"):
temp_image = sky_imager.original_image.copy()
temp_image[:, :, 0] = 255
temp_image[:, :, 1] = 255
temp_image[:, :, 2] = 255
image = sky_imager.crop_image(temp_image)
image = np.asarray(image)
image = image[:,:,::-1]
# cv2.imshow("image",image)
cv2.imwrite(output_folder + output_name, image)
print("Saved crop mask at: " + output_folder + output_name)
def save_crop_image(sky_imager,output_folder,output_name="crop_image.png"):
temp_image = sky_imager.original_image.copy()
image = sky_imager.crop_image(temp_image)
image = image[:,:,::-1]
cv2.imwrite(output_folder + output_name, image)
print("Saved cropped image at: " + output_folder + output_name)
def save_sun_mask(sky_imager,output_folder,output_name="sun_mask.png"):
temp_image = sky_imager.original_image.copy()
temp_image[:, :, 0] = 255
temp_image[:, :, 1] = 255
temp_image[:, :, 2] = 255
temp_image = sky_imager.crop_image(temp_image)
sun_mask = sky_imager.mask_around_sun
temp_image[:, :, 0][sun_mask] = 0
temp_image[:, :, 1][sun_mask] = 0
temp_image[:, :, 2][sun_mask] = 0
image = temp_image
image = rotate_image(image,25)
cv2.imwrite(output_folder + output_name, image)
print("Saved sun mask at: " + output_folder + output_name)
def save_sun_image(sky_imager,output_folder,output_name="sun_image.png"):
temp_image = sky_imager.image.copy()
temp_image = rotate_image(temp_image,example_rotation)
image = temp_image[:,:,::-1]
cv2.imwrite(output_folder + output_name, image)
print("Saved sun image at: " + output_folder + output_name)
def rotate_image(image, deg):
"""
Helper function to rotate images.
Args:
image:
deg:
Returns:
"""
rows, cols = (image.shape[0], image.shape[1])
M = cv2.getRotationMatrix2D((cols / 2, rows / 2), -deg, 1)
return cv2.warpAffine(image, M, (cols, rows))
def save_rotation_mask(sky_imager,output_folder,output_name="rotation_mask.png"):
angle_image_orig = sky_imager.angle_array[:,:,0].copy()
angle_image_offset = rotate_image(angle_image_orig,example_rotation)
fig = plt.figure(frameon=False)
w,h = sky_imager.get_image_size()
fig.set_size_inches(int(w/100), int(h/100))
ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.set_axis_off()
fig.add_axes(ax)
ax.imshow(angle_image_offset)
fig.savefig(output_folder+output_name, dpi=100)
plt.close()
print("Saved rotation mask at: " + output_folder + output_name)
def save_rotated_image(sky_imager,output_folder,output_name="rotation_image.png"):
temp_image = sky_imager.original_image.copy()
temp_image = sky_imager.crop_image(temp_image)
angle_image_offset = rotate_image(temp_image,example_rotation)
image = angle_image_offset[:,:,::-1]
cv2.imwrite(output_folder + output_name, image)
print("Saved rotated image at: " + output_folder + output_name)
def save_cloud_mask(sky_imager,output_folder,output_name="cloud_mask.png"):
cloud_mask = sky_imager.cloud_mask.copy()
cloud_mask = rotate_image(cloud_mask, example_rotation)
fig = plt.figure(frameon=False)
w, h = sky_imager.get_image_size()
fig.set_size_inches(int(w / 100), int(h / 100))
ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.set_axis_off()
fig.add_axes(ax)
ax.imshow(cloud_mask)
fig.savefig(output_folder + output_name, dpi=100)
plt.close()
print("Saved cloud mask at: " + output_folder + output_name)
def save_cloud_image(sky_imager,output_folder,output_name="cloud_image.png"):
cloud_image = sky_imager.cloud_image.copy()
cloud_image = rotate_image(cloud_image, example_rotation)
fig = plt.figure(frameon=False)
w, h = sky_imager.get_image_size()
fig.set_size_inches(int(w / 100), int(h / 100))
ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.set_axis_off()
fig.add_axes(ax)
ax.imshow(cloud_image)
fig.savefig(output_folder + output_name, dpi=100)
plt.close()
print("Saved cloud mask at: " + output_folder + output_name)
def save_cloud_map(sky_imager,output_folder,output_name="cloud_map.png"):
map = cmos.Map(lat_min=11.18, lat_max=11.30, lon_min=54.47, lon_max=54.53)
fig = plt.figure()
#w, h = sky_imager.get_image_size()
#fig.set_size_inches(int(w / 100), int(h / 100))
ax = plt.Axes(fig, [0., 0., 1., 1.])
fig.add_axes(ax)
ax = map.make_map(subplot_info=111,tile_resolution=13)
ax.set_positional_data(date=sky_imager.date,
cloud_height=sky_imager.cloud_height,
sun_azimuth=sky_imager.sun_azimuth,
sun_elevation=sky_imager.sun_elevation)
sky_imager.create_cloud_mask()
sky_imager.create_lat_lon_cloud_mask()
ax.create_shadow_mask(sky_imager.lat_lon_cloud_mask)
ax.add_shadows()
plt.tight_layout()
fig.savefig(output_folder + output_name, dpi=700)
plt.close()
print("Saved cloud map at: " + output_folder + output_name)
if __name__ == "__main__":
output_folder = "./"
file = "/home/fibu/Studium/18_SoSe/Lehrexkursion/Daten/LEX_WKM2_Image_20180826_112520_UTCp1.jpg"
sky_imager = cmos.SkyImager("hq")
sky_imager.get_date_from_image_name(file)
ceilo = cmos.Ceilometer()
cloud_height = ceilo.get_height(sky_imager.date)
sky_imager.load_image(file, cloud_height=cloud_height)
# Uebtertriebene Rotation zu Veranschauungszwecken:
global example_rotation
example_rotation = 25
# Diese funktionen simulieren einzeln in der richtigen Reihenfolge,
# wie das Programm funktioniert:
# save_orig_image(sky_imager,output_folder)
# save_crop_mask(sky_imager,output_folder)
# save_crop_image(sky_imager,output_folder)
# save_rotation_mask(sky_imager,output_folder)
# save_rotated_image(sky_imager,output_folder)
# save_sun_mask(sky_imager,output_folder)
# save_sun_image(sky_imager,output_folder)
# save_cloud_mask(sky_imager,output_folder)
# save_cloud_image(sky_imager,output_folder)
save_cloud_map(sky_imager,output_folder)